Currently, medical imaging methods generally analyze global changes in quantitative measures in response to a disease or treatment. A major disadvantage of these methods is that the effects of the measured disease/treatment get diluted due to global averaging and therefore, lose their strength for early detection. Recent advancements in digital medical imaging have opened avenues for quantitative analyses of different volumetric and morphometric indices in response to a disease or a treatment.
Although three dimensional (3D) anatomic atlas models exist, they are primarily for human brain imaging. The focus is to segment the different anatomic regions of interest (ROI) in a given human brain data and statistical analysis of the transformation to characterize different populations.
Alternatively, bone-related research works have studied disease or treatment induced regional structural changes. A longitudinal study of the effect of salmon calcitonin on trabecular bone (TB) architecture observed large regional variations in statistical significance for distinguishing remodeling changes in trabecular architecture due to treatment.
In a study involving 39 vertebral fracture and 70 age-matched control subjects, all post-menopausal women, it was demonstrated that radiography-based TB anisotropy parameters distinguished between fracture and control groups, showing further that different regions in the calcaneus had different statistical significance.
Further, peripheral quantitative computed tomography (pQCT) and micro-computed tomography (μCT) images of human cadaveric TB samples from the anterior/posterior and superior/inferior regions of the ultra-distal tibia and mid-femur neck, respectively, demonstrated regional differences in both BMD and micro-architectural parameters.
Recently, strong orientation differences were observed between the medial and lateral sides of axial cross sections in μMRI images of the human distal radius. Regional analysis of TB micro-architecture has also been found to distinguish between osteoarthritic and non-osteoarthritic women.
Accordingly, a major challenge in performing such analysis is the lack of technology for building a mean anatomic space (MAS) that allows analyzing data from a given subject in reference to an anatomic coordinate system. Such a system would provide an effective tool for point-by-point regional analysis and comparison of quantitative indices for data coming from a longitudinal or transverse study. Using an anatomic coordinate system would open several avenues for quantitative data analysis.
As an example, at the training phase, the computation of regional distributions of quantitative parameter(s) from two or more known populations (e.g., normal and different diseased groups) would be immediately ready for diagnostic purpose in a subject whose clinical status is unknown. Such a system would be useful for both cross sectional and longitudinal studies and for early diagnostic, and would be a vital tool for understanding regional response of a disease or treatment at various stages of its progression.